{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "# This allows multiple outputs from a single jupyter notebook cell:\n",
    "from IPython.core.interactiveshell import InteractiveShell\n",
    "InteractiveShell.ast_node_interactivity = \"all\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'1.0.3'"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "%matplotlib inline\n",
    "import pandas as pd\n",
    "pd.__version__  # for the record"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(252, 9)"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Open</th>\n",
       "      <th>High</th>\n",
       "      <th>Low</th>\n",
       "      <th>Close</th>\n",
       "      <th>Adj Close</th>\n",
       "      <th>Volume</th>\n",
       "      <th>UpperB</th>\n",
       "      <th>LowerB</th>\n",
       "      <th>PercentB</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Date</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2011-07-01</th>\n",
       "      <td>132.089996</td>\n",
       "      <td>134.100006</td>\n",
       "      <td>131.779999</td>\n",
       "      <td>133.919998</td>\n",
       "      <td>117.161659</td>\n",
       "      <td>202385700</td>\n",
       "      <td>132.373927</td>\n",
       "      <td>125.316073</td>\n",
       "      <td>1.219057</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2011-07-05</th>\n",
       "      <td>133.779999</td>\n",
       "      <td>134.080002</td>\n",
       "      <td>133.389999</td>\n",
       "      <td>133.809998</td>\n",
       "      <td>117.065437</td>\n",
       "      <td>165936000</td>\n",
       "      <td>133.254297</td>\n",
       "      <td>124.912703</td>\n",
       "      <td>1.066618</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2011-07-06</th>\n",
       "      <td>133.490005</td>\n",
       "      <td>134.139999</td>\n",
       "      <td>133.110001</td>\n",
       "      <td>133.970001</td>\n",
       "      <td>117.205429</td>\n",
       "      <td>143331600</td>\n",
       "      <td>134.040915</td>\n",
       "      <td>124.627085</td>\n",
       "      <td>0.992467</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                  Open        High         Low       Close   Adj Close  \\\n",
       "Date                                                                     \n",
       "2011-07-01  132.089996  134.100006  131.779999  133.919998  117.161659   \n",
       "2011-07-05  133.779999  134.080002  133.389999  133.809998  117.065437   \n",
       "2011-07-06  133.490005  134.139999  133.110001  133.970001  117.205429   \n",
       "\n",
       "               Volume      UpperB      LowerB  PercentB  \n",
       "Date                                                     \n",
       "2011-07-01  202385700  132.373927  125.316073  1.219057  \n",
       "2011-07-05  165936000  133.254297  124.912703  1.066618  \n",
       "2011-07-06  143331600  134.040915  124.627085  0.992467  "
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Open</th>\n",
       "      <th>High</th>\n",
       "      <th>Low</th>\n",
       "      <th>Close</th>\n",
       "      <th>Adj Close</th>\n",
       "      <th>Volume</th>\n",
       "      <th>UpperB</th>\n",
       "      <th>LowerB</th>\n",
       "      <th>PercentB</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Date</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2012-06-27</th>\n",
       "      <td>132.419998</td>\n",
       "      <td>133.429993</td>\n",
       "      <td>131.970001</td>\n",
       "      <td>133.169998</td>\n",
       "      <td>118.980804</td>\n",
       "      <td>108088000</td>\n",
       "      <td>136.447962</td>\n",
       "      <td>128.140042</td>\n",
       "      <td>0.605441</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2012-06-28</th>\n",
       "      <td>132.289993</td>\n",
       "      <td>132.990005</td>\n",
       "      <td>131.279999</td>\n",
       "      <td>132.789993</td>\n",
       "      <td>118.641281</td>\n",
       "      <td>169242100</td>\n",
       "      <td>136.500761</td>\n",
       "      <td>128.219241</td>\n",
       "      <td>0.551922</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2012-06-29</th>\n",
       "      <td>135.199997</td>\n",
       "      <td>136.270004</td>\n",
       "      <td>134.850006</td>\n",
       "      <td>136.100006</td>\n",
       "      <td>121.598610</td>\n",
       "      <td>212250900</td>\n",
       "      <td>136.721010</td>\n",
       "      <td>128.792993</td>\n",
       "      <td>0.921670</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                  Open        High         Low       Close   Adj Close  \\\n",
       "Date                                                                     \n",
       "2012-06-27  132.419998  133.429993  131.970001  133.169998  118.980804   \n",
       "2012-06-28  132.289993  132.990005  131.279999  132.789993  118.641281   \n",
       "2012-06-29  135.199997  136.270004  134.850006  136.100006  121.598610   \n",
       "\n",
       "               Volume      UpperB      LowerB  PercentB  \n",
       "Date                                                     \n",
       "2012-06-27  108088000  136.447962  128.140042  0.605441  \n",
       "2012-06-28  169242100  136.500761  128.219241  0.551922  \n",
       "2012-06-29  212250900  136.721010  128.792993  0.921670  "
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = pd.read_csv('../data/SPY_20110701_20120630_Bollinger.csv',index_col=0,parse_dates=True)\n",
    "#df = df.loc['2012-01-01':,:]\n",
    "df.shape\n",
    "df.head(3)\n",
    "df.tail(3)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "---\n",
    "\n",
    "#### Using this dataframe, we can of course plot a basic ohlc or candlestick plot:\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 576x414 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import mplfinance as mpf\n",
    "\n",
    "mpf.plot(df,volume=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "---\n",
    "\n",
    "Let's say we want to plot the Lower Bollinger band along with the basic OHLCV plot.  \n",
    "\n",
    "We use `make_addplot()` to create the addplot dict, and pass that into the plot() function:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 576x414 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "apdict = mpf.make_addplot(df['LowerB'])\n",
    "\n",
    "mpf.plot(df,volume=True,addplot=apdict)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "---\n",
    "\n",
    "When creating the `addplot` dict, we can specify that we want a scatter plot:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 576x414 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "apd = mpf.make_addplot(df['LowerB'],scatter=True)\n",
    "\n",
    "mpf.plot(df,addplot=apd)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "---\n",
    "\n",
    "The above example is a trivial use of a scatter plot, where the default line plot makes more sense.  \n",
    "\n",
    "A more helpful use of a scatter plot might be to highlight specific movements in the data.  For example, let's say we want to highlight whenever the \"Percent B\" Bollinger metric drops below zero.  To do this, let's first calculate a series that contains this information:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "def percentB_belowzero(percentB,price):\n",
    "    import numpy as np\n",
    "    signal   = []\n",
    "    previous = -1.0\n",
    "    for date,value in percentB.iteritems():\n",
    "        if value < 0 and previous >= 0:\n",
    "            signal.append(price[date]*0.99)\n",
    "        else:\n",
    "            signal.append(np.nan)\n",
    "        previous = value\n",
    "    return signal"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "---\n",
    "Take a small data set, and calculate a series that shows when the percentB falls below zero:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "tdf = df.loc['05-10-2012':'06-07-2012',]  # Take a smaller data set so it's easier to see the scatter points\n",
    "\n",
    "signal = percentB_belowzero(tdf['PercentB'], tdf['Close'])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "---\n",
    "\n",
    "Now plot the calculated information as an additional scatter plot on top of the the OHLC data:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 576x414 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "apd = mpf.make_addplot(signal,scatter=True)\n",
    "\n",
    "mpf.plot(tdf,addplot=apd)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "---\n",
    "\n",
    "We can customize the marker size and shape, to make the scatter markers easier to see:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "20"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "text/plain": [
       "[nan,\n",
       " nan,\n",
       " 132.76890099000002,\n",
       " nan,\n",
       " nan,\n",
       " 129.55140099000002,\n",
       " nan,\n",
       " nan,\n",
       " nan,\n",
       " nan,\n",
       " nan,\n",
       " nan,\n",
       " nan,\n",
       " nan,\n",
       " nan,\n",
       " 126.87840395999999,\n",
       " nan,\n",
       " nan,\n",
       " nan,\n",
       " nan]"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(signal)\n",
    "signal"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "#STOP HERE"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "ty = tdf['Close'] - 132.3"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "    ==================================================\n",
      "    Don't forget to implement `set_ylim` for addplot()\n",
      "    ==================================================\n",
      "    \n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 576x414 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 576x414 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "print(\n",
    "    '''\n",
    "    ==================================================\n",
    "    Don't forget to implement `set_ylim` for addplot()\n",
    "    ==================================================\n",
    "    '''\n",
    ")\n",
    "apd = [ mpf.make_addplot(signal,type='bar',markersize=200,marker='^',panel='A'),\n",
    "        #mpf.make_addplot(df['Close'],bar=True,panel='B',secondary_y=False)\n",
    "       mpf.make_addplot(ty,type='bar',panel='B')#,secondary_y=False)\n",
    "      ]\n",
    "\n",
    "mpf.plot(tdf,addplot=apd,set_ylim=(126,138),panel_order='ABC',\n",
    "         set_ylim_panelB=(-7,+7),panel_ratio=(1,1,2))\n",
    "\n",
    "mpf.plot(tdf,addplot=apd,set_ylim=(126,138),panel_order='ABC',panel_ratio=(1,1,2))\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.4"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}
